| Title: |
Modeling snowpack dynamics and surface energy budget in boreal and subarctic peatlands and forests |
| Authors: |
Nousu, Jari Pekka; Lafaysse, Matthieu; Mazzotti, Giulia; Ala-aho, Pertti; Marttila, Hannu; Cluzet, Bertrand; Aurela, Mika; Lohila, Annalea; Kolari, Pasi; Boone, Aaron; Fructus, Mathieu; Launiainen, Samuli |
| Contributors: |
Institute for Atmospheric and Earth System Research (INAR); Micrometeorology and biogeochemical cycles; Ecosystem processes (INAR Faculty of Agriculture and Forestry) |
| Publisher Information: |
Copernicus GMBH |
| Publication Year: |
2024 |
| Collection: |
Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto |
| Subject Terms: |
Physical sciences; Ecology; evolutionary biology; Forestry; Computer and information sciences |
| Description: |
The snowpack has a major influence on the land surface energy budget. Accurate simulation of the snowpack energy and radiation budget is challenging due to, e.g., effects of vegetation and topography, as well as limitations in the theoretical understanding of turbulent transfer in the stable boundary layer. Studies that evaluate snow, hydrology and land surface models against detailed observations of all surface energy balance components at high latitudes are scarce. In this study, we compared different configurations of the SURFEX land surface model against surface energy flux, snow depth and soil temperature observations from four eddy-covariance stations in Finland. The sites cover two different climate and snow conditions, representing the southern and northern subarctic zones, as well as the contrasting forest and peatland ecosystems typical for the boreal landscape. We tested different turbulent flux parameterizations implemented in the Crocus snowpack model. In addition, we examined common alternative approaches to conceptualize soil and vegetation, and we assessed their performance in simulating surface energy fluxes, snow conditions and soil thermal regime. Our results show that a stability correction function that increases the turbulent exchange under stable atmospheric conditions is imperative to simulate sensible heat fluxes over the peatland snowpacks and that realistic peat soil texture (soil organic content) parameterization greatly improves the soil temperature simulations. For accurate simulations of surface energy fluxes, snow and soil conditions in forests, an explicit vegetation representation is necessary. Moreover, we demonstrate the high sensitivity of surface fluxes to a poorly documented parameter involved in snow cover fraction computation. Although we focused on models within the SURFEX platform, the results have broader implications for choosing suitable turbulent flux parameterization and model structures depending on the potential use cases for high-latitude land surface modeling. ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| ISBN: |
978-85-18-40801-3; 85-18-40801-6 |
| Relation: |
This work was funded by the Research Council of Finland (RCF) (ArcI Profi 4). Giulia Mazzotti was funded by the Swiss National Science Foundation (grant no. P500PN_202741). Samuli Launiainen and Jari-Pekka Nousu acknowledge the GreenFeedBack project from the EU Horizon Europe Framework Programme for Research and Innovation (grant no. 101056921). Samuli Launiainen acknowledges the support of RCF (LS-HYDRO, 356138). Pertti Ala-aho was funded by the RCF Research Fellow grant (no. 347348). Pasi Kolari, Mika Aurela and Annalea Lohila acknowledge the support of the ACCC Flagship funded by the RCF (no. 337549 and no. 337552) and ICOS Finland by the University of Helsinki and the Ministry of Transport and Communication. Mika Aurela and Annalea Lohila also acknowledge the RCF (UPFORMET, grant no. 308511). Jari-Pekka Nousu thanks Riitta ja Jorma Takasen säätiö for the internationalization support grant. The authors would like to thank Bertrand Decharme, Christine Delire, and Bertrand Bonan at CNRM/GAME and Marie Dumont at CNRM/CEN for their great support during this work. CNRM/CEN is part of Labex OSUG@2020. This research has been supported by the Academy of Finland (ArcI Profi 4), the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (grant no. P500PN_202741), Horizon 2020 (grant no. 101056921), RCF (LS-HYDRO, 356138 and UPFORMET, grant no. 308511) and the Academy of Finland (grant nos. 347348, 337549, and 337552).; https://hdl.handle.net/10138/574302; 85184080167; 001166581000001 |
| Availability: |
https://hdl.handle.net/10138/574302 |
| Rights: |
cc_by ; info:eu-repo/semantics/openAccess ; openAccess |
| Accession Number: |
edsbas.EB2FA82C |
| Database: |
BASE |